State-of-the-Art Review on Relevance of Genetic Algorithm to Internet Web Search

Author:

Agbele Kehinde1,Adesina Ademola1,Ekong Daniel2,Ayangbekun Oluwafemi3

Affiliation:

1. Department of Computer Science, Soft Computing and Intelligent Systems Research Group, University of the Western Cape, Private Bag X17, Bellville, Cape Town, South Africa

2. Department of Mathematical Sciences (Computer Science Option), Ekiti State University, Ado-Ekiti, PMB 5363, Ado-Ekiti, Ekiti State, Nigeria

3. College of Information and Communication Technology, Crescent University, Abeokuta, Ogun-State, Nigeria

Abstract

People use search engines to find information they desire with the aim that their information needs will be met. Information retrieval (IR) is a field that is concerned primarily with the searching and retrieving of information in the documents and also searching the search engine, online databases, and Internet. Genetic algorithms (GAs) are robust, efficient, and optimizated methods in a wide area of search problems motivated by Darwin’s principles of natural selection and survival of the fittest. This paper describes information retrieval systems (IRS) components. This paper looks at how GAs can be applied in the field of IR and specifically the relevance of genetic algorithms to internet web search. Finally, from the proposals surveyed it turns out that GA is applied to diverse problem fields of internet web search.

Publisher

Hindawi Limited

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Civil and Structural Engineering,Computational Mechanics

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Relevance Feedback using Genetic Algorithm on Information Retrieval for Indonesian Language Documents;Journal of Information Systems Engineering and Business Intelligence;2019-10-24

2. Efficiency of genetic algorithm for subject search queries;Lobachevskii Journal of Mathematics;2016-05

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